> unless 100% of the population is administered a test with no risk of false negative or positives. Actually, the "risk" of false positives or false negatives

> unless 100% of the population is administered a test with no risk of false negative or positives. Actually, the "risk" of false positives or false negatives is dependent on prevalence, 100% is not always required. If you have a test where 5 of 100 cases are false (i.e. 95% times is not wrong), and nobody of these tested is actually infected, you could incorrectly believe that 5% of population is infected even when nobody is, meaning such a conclusion would be completely false. But if the population is actually already e.g. 50% infected, the same test can "lie" only 5%, giving you 47% or 53% but still being "mostly true" (from the engineering point of view). So it is important to ignore the test reports as long as they are close to their false positive rate, which they were in a lot of antibody tests done up to now. Also "false positives" and "false negatives" can lead to wrong handling of the cases, but that's another topic.